Kuo-Jung Lee

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A common objective of fMRI (functional magnetic resonance imaging) studies is to determine subject-specific areas of increased blood oxygenation level dependent (BOLD) signal contrast in response to a stimulus or task, and hence to infer regional neuronal activity. We posit and investigate a Bayesian approach that incorporates spatial and temporal(More)
a Department of Business Management, National Sun Yat-sen University, 70, Lienhai Rd., Kaohsiung 80424, Taiwan, R.O.C. b Department of Commerce Automation and Management, National Pingtung Institute of Commerce, 51, Minsheng E. Rd., Pingtung City 90004, Taiwan, R.O.C. c Department of Finance, National Sun Yat-sen University, 70, Lienhai Rd. Kaohsiung 80424,(More)
We propose a Bayesian method for variable selection in the finite mixture model of linear regressions. The model assumes that the observations come from a heterogeneous population which is a mixture of a finite number of sub-populations. Within each sub-population, the response variable can be explained by a linear regression on the predictor variables. So(More)
This paper applies real options analysis to analyze the optimal decision of adopting e-commerce when a firm’s output price is uncertain. The traditional discount cash flow method ignores the value of timing and operational flexibility. Therefore, it might underestimate the value of adopting e-commerce. The paper is the first study to build a theoretical(More)
One of the major objectives of functional magnetic resonance imaging studies is to infer regional neuronal activity in response to a stimulus or task. We consider a Bayesian approach which incorporates spatial and temporal dependence and allows for the task-related response to change dynamically over the scanning session. AMS 2000 subject classifications:(More)
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